This project establishes an interdisciplinary network of investigators and focuses their work on the common goal of studying the dynamic brain processes underlying deployment of attention and subsequent selective processing of target stimuli. The overall goals of this project are to devise and execute an interdisciplinary study of attention and to use this opportunity to evaluate and expand the state-of-the-art signal processing, computational and modeling procedures employed in this project. The research is based upon a theoretical framework for directing attention grounded in behavioral, lesion, animal and physiological information. We utilize multi-modality functional imaging with fMRI and EEG measures during cued attention experiments, combined with advanced analyses from many perspectives to determine the spatial and temporal interplay of brain regions underlying attention. Following standard analyses of fMRI and EEG data we perform brain source localization of EEG data in combination with fMRI data as may be appropriate. Applications of advanced signal analyses include methods focused on extracting task-specific activity patterns based on pre-specified statistical hypotheses (e.g., Partial Least Squares, PLS) and methods that characterize all dimensions of the data, identifying potentially functionally distinct activity components that were not otherwise obvious from the outset (Independent Component Analysis, ICA). Model-based and model free methods for examining functional and effective connectivity between brain regions will be applied to the rich spatial and temporal data obtained with the fMRI and EEG recordings. Another goal will be to compare the multiple tools employed and to develop methods for optimally integrating them for studies of attention and other cognitive neuroscience domains. The investigators will meet regularly and work with the consultants regarding extension of the network to include cognitive and human neuropsychological studies, large scale modeling, and animal studies.